Alarconpy: A Python Package for Meteorologists
Authors/Creators
- 1. Departamento de Meteorología, Instituto Superior de Tecnologías y Ciencias Aplicadas, Universidad de La Habana, 10400 La Habana, Cuba
Description
Alarconpy is a tools collection in Python programming language that offers many functions and algorithms for several meteorological applications as well as for quickly processing weather data.
Software repository on Github
Alarconpy is developed for Python 3.x and there are some python libraries required for use it:
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Numpy: It is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated functions and useful linear algebra, Fourier transform, and random number capabilities. The NumPy array object is the common interface for working with typed arrays of data across a wide-variety of scientific Python packages. NumPy also features a C-API, which enables interfacing existing Fortran/C/C++ libraries with Python and NumPy (https://www.scipy.org).
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Metpy: It is a modern meteorological open-source toolkit for Python. It is a maintained project of Unidata to serve the academic meteorological community. MetPy consists of three major areas of functionality: Plots, Calculations and File Input/Output (https://unidata.github.io/MetPy/latest/index.html)
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Cartopy: It is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses. It makes use of the powerful PROJ.4, NumPy and Shapely libraries and includes a programmatic interface built on top of Matplotlib for the creation of publication quality maps.
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Scipy: It is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines, such as routines for numerical integration, interpolation, optimization, linear algebra, and statistics.
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NetCDF4: It is the Python interface to the netCDF C library. This module can read and write files in both the new netCDF 4 and the old netCDF 3 format, and can create files that are readable by HDF5 clients (https://unidata.github.io/netcdf4-python/netCDF4/index.html).
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Matplotlib: It is a plotting library for the Python programming language and its numerical mathematics extension NumPy (https://matplotlib.org). Also, it is a sophisticated library capable of producing publication-quality graphics in a variety of formats, and with full LaTeX support.
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Time: This module provides various time-related functions (https://docs.python.org/3/library/time.html.
Installation
We recommend using the Alarconpy package in the Anaconda environment. Just clone the Alarconpy repository
git clone https://github.com/apalarcon/alarconpy.git
and copy the alarconpy folder into alarconpy clone to the anaconda path installation
path_to_anaconda_installation/lib/python3.x/site-packages/
Please check that you have installed all dependencies needed for Alarconpy.
Files
alarconpy_paper.pdf
Files
(236.4 MB)
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Additional details
Identifiers
References
- Chavas, D. R., Lin, N., and Emanuel, K. A. (2015). A model for the complete radial structure of the tropical cyclone wind field. part i: Comparison with observed structure. Journal of the Atmospheric Sciences, 72:3647–3662. https://doi.org/110.1175/JAS-D-15-0014.1
- DeMaria, M. (1987). Tropical cyclone track prediction with a barotropic spectral model. Monthly Weather Review, 115:2346–2357. https://doi/org/10.1175/1520-0493(1987)115,2346:TCTPWA.2.0.CO;2
- Emanuel, K. and Rotunno, R. (2011). Self-stratification of tropical cyclone outflow. Part I: Implications for storm structure. Journal of the Atmospheric Sciences, 68:82236–2249. https://doi.org/10.1175/JAS-D-10-05024.1
- Emanuel, K. A. (2004). Tropical cyclones energetics and structure. Atmospheric Turbulence and Mesoscale Meteorology. E. Fedorovich,R. Rotunno, and B. Stevens, Eds., Cambridge University Press, page 165–192. http://texmex.mit.edu/pub/emanuel/PAPERS/Energetics_Structure.pdf
- Frisius, T. and Scgönemann, D. (2013). The impact of gradient wind imbalance on potential intensity of tropical cyclones in an unbalanced slab boundary layer model. Journal of the Atmospheric Sciences, 70:1874–1890. https://doi.org/10.1175/JAS-D-12-0160.1
- Holland, G. J. (1980). An analytic model of the wind and pressure profiles in hurricanes. Monthly Weather Review, 1008:1212–1218. https://doi.org/10.1175/1520-0493(1980)108,1212:AAMOTW.2.0.CO;2
- Willoughby, H. E., Darling, R. W. R., and Rahn, M. (2006). Parametric representation of the primary hurricane vortex. Part II: A new family of sectionally continuous profiles. Monthly Weather Review, 134:1102–1120. https://doi.org/10.1175/MWR3106.1